An Efficient Approach for Extraction Positive and Negative Association Rules from Big Data

Parfait Bemarisika, Harrimann Ramanantsoa, André Totohasina. An Efficient Approach for Extraction Positive and Negative Association Rules from Big Data. In Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar R. Weippl, editors, Machine Learning and Knowledge Extraction - Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Hamburg, Germany, August 27-30, 2018, Proceedings. Volume 11015 of Lecture Notes in Computer Science, pages 79-97, Springer, 2018. [doi]

@inproceedings{BemarisikaRT18,
  title = {An Efficient Approach for Extraction Positive and Negative Association Rules from Big Data},
  author = {Parfait Bemarisika and Harrimann Ramanantsoa and André Totohasina},
  year = {2018},
  doi = {10.1007/978-3-319-99740-7_6},
  url = {https://doi.org/10.1007/978-3-319-99740-7_6},
  researchr = {https://researchr.org/publication/BemarisikaRT18},
  cites = {0},
  citedby = {0},
  pages = {79-97},
  booktitle = {Machine Learning and Knowledge Extraction - Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Hamburg, Germany, August 27-30, 2018, Proceedings},
  editor = {Andreas Holzinger and Peter Kieseberg and A Min Tjoa and Edgar R. Weippl},
  volume = {11015},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-99740-7},
}